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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Early prediction of remaining useful life for Lithium-ion batteries based on a hybrid machine learning method
Zheming Tong, Jiazhi Miao, Shuiguang Tong, et al.
Journal of Cleaner Production (2021) Vol. 317, pp. 128265-128265
Closed Access | Times Cited: 120

Showing 26-50 of 120 citing articles:

A hybrid approach based on deep neural network and double exponential model for remaining useful life prediction
Junyuan Liang, Hui Liu, Ning‐Cong Xiao
Expert Systems with Applications (2024) Vol. 249, pp. 123563-123563
Closed Access | Times Cited: 11
Progress of machine learning in materials design for Li-Ion battery
Prasshanth C.V., Arun Kumar Lakshminarayanan, R. Brindha, et al.
Next Materials (2024) Vol. 2, pp. 100145-100145
Open Access | Times Cited: 10
Leveraging machine learning in porous media
Mostafa Delpisheh, Benyamin Ebrahimpour, Abolfazl Fattahi, et al.
Journal of Materials Chemistry A (2024) Vol. 12, Iss. 32, pp. 20717-20782
Open Access | Times Cited: 8
Quantifying key factors for optimised manufacturing of Li-ion battery anode and cathode via artificial intelligence
Mona Faraji Niri, Kailong Liu, Geanina Apachitei, et al.
Energy and AI (2021) Vol. 7, pp. 100129-100129
Open Access | Times Cited: 49
Life prediction model for lithium-ion battery considering fast-charging protocol
Chen Zhang, Hongmin Wang, Lifeng Wu
Energy (2022) Vol. 263, pp. 126109-126109
Closed Access | Times Cited: 33
Prognostics of Remaining Useful Life for Lithium-Ion Batteries Based on Hybrid Approach of Linear Pattern Extraction and Nonlinear Relationship Mining
Yingzhou Wang, Chenyang Hei, Hui Liu, et al.
IEEE Transactions on Power Electronics (2022) Vol. 38, Iss. 1, pp. 1054-1063
Closed Access | Times Cited: 32
Prediction of Li-ion battery capacity degradation considering polarization recovery with a hybrid ensemble learning model
Zheming Tong, Jiazhi Miao, Jiale Mao, et al.
Energy storage materials (2022) Vol. 50, pp. 533-542
Closed Access | Times Cited: 29
Latest innovations in the field of condition-based maintenance of rotatory machinery: a review
Anil Kumar, Chander Parkash, Hesheng Tang, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 2, pp. 022003-022003
Closed Access | Times Cited: 20
Capacity and remaining useful life prediction for lithium-ion batteries based on sequence decomposition and a deep-learning network
Zili Wang, Yonglu Liu, Fen Wang, et al.
Journal of Energy Storage (2023) Vol. 72, pp. 108085-108085
Closed Access | Times Cited: 19
A novel hybrid model for lithium-ion batteries lifespan prediction with high accuracy and interpretability
Xiaoxian Pang, Wei Yang, Chengyun Wang, et al.
Journal of Energy Storage (2023) Vol. 61, pp. 106728-106728
Closed Access | Times Cited: 18
A Flexible deep convolutional neural network coupled with progressive training framework for online capacity estimation of lithium-ion batteries
Qiao Xue, Junqiu Li, Yansheng Xiao, et al.
Journal of Cleaner Production (2023) Vol. 397, pp. 136575-136575
Closed Access | Times Cited: 17
Lithium-Ion Battery State of Health Estimation with Multi-Feature Collaborative Analysis and Deep Learning Method
Xianbin Yang, Bin Ma, Haicheng Xie, et al.
Batteries (2023) Vol. 9, Iss. 2, pp. 120-120
Open Access | Times Cited: 16
ICFormer: A Deep Learning model for informed lithium-ion battery diagnosis and early knee detection
Nahuel Costa, David Anseán, Matthieu Dubarry, et al.
Journal of Power Sources (2023) Vol. 592, pp. 233910-233910
Open Access | Times Cited: 16
A model-data-fusion method for real-time continuous remaining useful life prediction of lithium batteries
Jinrui Zhang, Dongzhen Lyu, Jiawei Xiang
Measurement (2024) Vol. 238, pp. 115312-115312
Closed Access | Times Cited: 6
A review of new technologies for lithium-ion battery treatment
Yao Li, Pengcheng Zhao, Boxiong Shen
The Science of The Total Environment (2024) Vol. 951, pp. 175459-175459
Closed Access | Times Cited: 6
Aging trajectory and end-of-life prediction for lithium-ion battery via similar fragment extraction of capacity degradation curves
Shuzhi Zhang, Shaojie Wu, Ganglin Cao, et al.
Journal of Cleaner Production (2024) Vol. 436, pp. 140686-140686
Closed Access | Times Cited: 5
Research on Hybrid Data-Driven Method for Predicting the Remaining Useful Life of Lithium-Ion Batteries
Y. G. Li, Liping Li, Lei Li, et al.
Computer Physics Communications (2025), pp. 109500-109500
Closed Access
Inconsistency analysis and comprehensive performance quantization of lithium-ion battery module configurations considering multi-factor cell-to-cell variation
Zheming Tong, Jun Zhang, Xing Chen
Journal of Energy Storage (2025) Vol. 114, pp. 115669-115669
Closed Access
Remaining Useful Life Early Prediction of Batteries Based on the Differential Voltage and Differential Capacity Curves
Sajad Saraygord Afshari, Shihao Cui, Xiangyang Xu, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 71, pp. 1-9
Closed Access | Times Cited: 39
The machine learning in lithium-ion batteries: A review
Liyuan Zhang, Zijun Shen, S. Mohammad Sajadi, et al.
Engineering Analysis with Boundary Elements (2022) Vol. 141, pp. 1-16
Closed Access | Times Cited: 25
RETRACTED:Machine-learning optimization of an innovative design of a Li-ion battery arrangement cooling system
Mohamed Boujelbene, Marjan Goodarzi, Masood Ashraf Ali, et al.
Journal of Energy Storage (2022) Vol. 58, pp. 106331-106331
Closed Access | Times Cited: 25
Machine learning in energy chemistry: introduction, challenges and perspectives
Yuzhi Xu, Jiankai Ge, Cheng‐Wei Ju
Energy Advances (2023) Vol. 2, Iss. 7, pp. 896-921
Open Access | Times Cited: 15
Physics-informed ensemble deep learning framework for improving state of charge estimation of lithium-ion batteries
Hanqing Yu, Zhengjie Zhang, Kaiyi Yang, et al.
Journal of Energy Storage (2023) Vol. 73, pp. 108915-108915
Closed Access | Times Cited: 15
Remaining useful life prediction for lithium-ion batteries with an improved grey particle filter model
Zhicun Xu, Naiming Xie, Kailing Li
Journal of Energy Storage (2023) Vol. 78, pp. 110081-110081
Closed Access | Times Cited: 15
An experimental investigation and hybrid neural network modelling of thermal management of lithium-ion batteries using a non-paraffinic organic phase change material, Myristyl alcohol
Muthya Goud Vempally, G. Satyanarayana, Janani Ramesh, et al.
Journal of Energy Storage (2023) Vol. 72, pp. 108395-108395
Closed Access | Times Cited: 13

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